Data and Statistics Foundation for Investment Professionals (Coursera)

In this course you will learn how to:

- Explain basic statistical measures and their application to real-life data sets

- Calculate and interpret measures of dispersion and explain deviations from a normal distribution

- Understand the use and appropriateness of different distributions

- Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary)

- Explain sampling theory and draw inferences about population parameters from sample statistics

- Formulate hypotheses on investment problems

Course 1 of 3 in the Data Science for Investment Professionals Specialization.
What You Will Learn

- Demonstrate the importance of and techniques for presenting data and the “data story”

- Understand data distributions and the importance and use of statistical measures

- Use statistical sampling and hypothesis testing to gain insight into population parameters

- Calculate data statistics and produce visualizations using Python

Syllabus

WEEK 1

Welcome to Data and Statistics Foundation for Investment Professionals

Measures of Central Tendency

WEEK 2

Measures of Dispersion

WEEK 3

Distributions

WEEK 4

Data Visualization Techniques

WEEK 5

Sampling Theory

WEEK 6

Hypothesis Testing

WEEK 7

Final Project

The final project places you in the role of a junior analyst who has been presented with data and needs to manipulate it in a meaningful way and present your findings to your manager in a well written report. It will test many of the things, including Python, that you have learned throughout this course. This final assessment is worth a maximum of 40% (out of a total of 100%) and counts towards your success in this course.